epiworldR (version 0.8.2.0)

tool: Tools in epiworld

Description

Tools are functions that affect how agents react to the virus. They can be used to simulate the effects of vaccination, isolation, and social distancing.

Usage

tool(
  name,
  prevalence,
  as_proportion,
  susceptibility_reduction,
  transmission_reduction,
  recovery_enhancer,
  death_reduction
)
set_name_tool(tool, name)
get_name_tool(tool)
add_tool(model, tool, proportion)
rm_tool(model, tool_pos)
tool_fun_logit(vars, coefs, model)
set_susceptibility_reduction(tool, prob)
set_susceptibility_reduction_ptr(tool, model, param)
set_susceptibility_reduction_fun(tool, model, tfun)
set_transmission_reduction(tool, prob)
set_transmission_reduction_ptr(tool, model, param)
set_transmission_reduction_fun(tool, model, tfun)
set_recovery_enhancer(tool, prob)
set_recovery_enhancer_ptr(tool, model, param)
set_recovery_enhancer_fun(tool, model, tfun)
set_death_reduction(tool, prob)
set_death_reduction_ptr(tool, model, param)
set_death_reduction_fun(tool, model, tfun)
# S3 method for epiworld_agents_tools
print(x, max_print = 10, ...)
set_distribution_tool(tool, distfun)
distribute_tool_randomly(prevalence, as_proportion, agents_ids = integer(0))
distribute_tool_to_set(agents_ids)

Value

• The tool function creates a tool of class epiworld_tool.

• The set_name_tool function assigns a name to the tool of class epiworld_tool and returns the tool.

• The get_name_tool function returns the name of the tool of class epiworld_tool.

• The rm_tool function removes the specified tool from a model.

• The set_susceptibility_reduction function assigns a probability reduction to the specified tool of class epiworld_tool.

• The set_transmission_reduction function assigns a probability reduction to the specified tool of class epiworld_tool.

• The set_recovery_enhancer function assigns a probability increase to the specified tool of class epiworld_tool.

• The set_death_reduction function assigns a probability decrease to the specified tool of class epiworld_tool.

• The distribute_tool_randomly function returns a distribution function of class epiworld_tool_distfun. When agents_ids is not empty, it will distribute the tool randomly within that set. Otherwise it uses all the agents in the model.

• The distribute_tool_to_set function returns a distribution function of class epiworld_tool_distfun.

Arguments

name

Name of the tool

prevalence

Numeric scalar. Prevalence of the tool.

as_proportion

Logical scalar. If TRUE, prevalence is interpreted as a proportion of the total number of agents in the model.

susceptibility_reduction

Numeric. Proportion it reduces susceptibility.

transmission_reduction

Numeric. Proportion it reduces transmission.

recovery_enhancer

Numeric. Proportion it improves recovery.

death_reduction

Numeric. Proportion it reduces probability of death.e

tool

An object of class epiworld_tool

model

Model

proportion

Deprecated.

tool_pos

Positive integer. Index of the tool's position in the model.

vars

Integer vector. Indices (starting from 0) of the positions of the variables used to compute the logit probability.

coefs

Numeric vector. Of the same length of vars, is a vector of coefficients associated to the logit probability.

prob

Numeric scalar. A probability (between zero and one).

param

Character scalar. Name of the parameter featured in model that will be added to the tool (see details).

tfun

An object of class epiworld_tool_fun.

x

An object of class epiworld_agents_tools.

max_print

Numeric scalar. Maximum number of tools to print.

...

Currently ignored.

distfun

An object of class epiworld_tool_distfun.

agents_ids

Integer vector. Indices of the agents to which the tool will be assigned.

Details

The name of the epiworld_tool object can be manipulated with the functions set_name_tool() and get_name_tool().

The add_tool function adds the specified tool to the model of class epiworld_model with specified proportion.

In the case of set_susceptibility_reduction_ptr, set_transmission_reduction_ptr, set_recovery_enhancer, and set_death_reduction_ptr, the corresponding parameters are passed as a pointer to the tool. The implication of using pointers is that the values will be read directly from the model object, so changes will be reflected.

The set_distribution_tool function assigns a distribution function to the specified tool of class epiworld_tool. The distribution function can be created using the functions distribute_tool_randomly() and distribute_tool_to_set().

The distribute_tool_randomly function creates a distribution function that randomly assigns the tool to a proportion of the population.

The distribute_tool_to_set function creates a distribution function that assigns the tool to a set of agents.

Examples

# Simple model
model_sirconn <- ModelSIRCONN(
  name                = "COVID-19",
  n                   = 10000,
  prevalence          = 0.01,
  contact_rate        = 5,
  transmission_rate   = 0.4,
  recovery_rate       = 0.95
)

# Running and printing
run(model_sirconn, ndays = 100, seed = 1912)
plot(model_sirconn)

epitool <- tool(
  name = "Vaccine",
  prevalence = 0.5,
  as_proportion = TRUE,
  susceptibility_reduction = .9,
  transmission_reduction = .5,
  recovery_enhancer = .5,
  death_reduction = .9
)

epitool

set_name_tool(epitool, "Pfizer") # Assigning name to the tool
get_name_tool(epitool) # Returning the name of the tool
add_tool(model_sirconn, epitool)
run(model_sirconn, ndays = 100, seed = 1912)
model_sirconn
plot(model_sirconn)

# To declare a certain number of individuals with the tool
rm_tool(model_sirconn, 0) # Removing epitool from the model
# Setting prevalence to 0.1
set_distribution_tool(epitool, distribute_tool_randomly(0.1, TRUE))
add_tool(model_sirconn, epitool)
run(model_sirconn, ndays = 100, seed = 1912)

# Adjusting probabilities due to tool
set_susceptibility_reduction(epitool, 0.1) # Susceptibility reduction
set_transmission_reduction(epitool, 0.2) # Transmission reduction
set_recovery_enhancer(epitool, 0.15) # Probability increase of recovery
set_death_reduction(epitool, 0.05) # Probability reduction of death

rm_tool(model_sirconn, 0)
add_tool(model_sirconn, epitool)
run(model_sirconn, ndays = 100, seed = 1912) # Run model to view changes


# Using the logit function --------------
sir <- ModelSIR(
  name = "COVID-19", prevalence = 0.01,
  transmission_rate = 0.9, recovery_rate = 0.1
)

# Adding a small world population
agents_smallworld(
  sir,
  n = 10000,
  k = 5,
  d = FALSE,
  p = .01
)

# Creating a tool
mask_wearing <- tool(
  name = "Mask",
  prevalence               = 0.5,
  as_proportion            = TRUE,
  susceptibility_reduction = 0.0,
  transmission_reduction   = 0.3, # Only transmission
  recovery_enhancer        = 0.0,
  death_reduction          = 0.0
)

add_tool(sir, mask_wearing)

run(sir, ndays = 50, seed = 11)
hist_0 <- get_hist_total(sir)

# And adding features
dat <- cbind(
  female = sample.int(2, 10000, replace = TRUE) - 1,
  x      = rnorm(10000)
)

set_agents_data(sir, dat)

# Creating the logit function
tfun <- tool_fun_logit(
  vars  = c(0L, 1L),
  coefs = c(-1, 1),
  model = sir
)

# The infection prob is lower
hist(plogis(dat %*% rbind(.5, 1)))

tfun # printing


set_susceptibility_reduction_fun(
  tool  = get_tool(sir, 0),
  model = sir,
  tfun  = tfun
)

run(sir, ndays = 50, seed = 11)
hist_1 <- get_hist_total(sir)

op <- par(mfrow = c(1, 2))
plot(hist_0)
abline(v = 30)
plot(hist_1)
abline(v = 30)
par(op)